Clustering Techniques Questions and Answers

Q: Agglomerative approach of clustering is one of the..........methods.

Agglomerative clustering is a hierarchical method.Agglomerative clustering works bottom-up: each object starts as its own cluster, and at every step the two closest clusters are merged, until one cluster remains or a stopping condition is met. The result is a hierarchy of clusters, drawn as a dendrogram. Its top-down counterpart, divisive clustering, is the other hierarchical approach.Partitioning methods such as k-means divide the data into a fixed number of clusters directly. Density-based methods such as DBSCAN grow clusters from dense regions, and model-based methods fit statistical models such as Gaussian mixtures.

Agglomerative approach of clustering is one of the..........methods.

A.Density
B.Partitioning
C.Hierarchical
D.Model based

Exam Year(s)

MH SET - 2023, SET Exam - 2023,

Answer: C

Agglomerative clustering is a hierarchical method.

Agglomerative clustering works bottom-up: each object starts as its own cluster, and at every step the two closest clusters are merged, until one cluster remains or a stopping condition is met. The result is a hierarchy of clusters, drawn as a dendrogram. Its top-down counterpart, divisive clustering, is the other hierarchical approach.

Partitioning methods such as k-means divide the data into a fixed number of clusters directly. Density-based methods such as DBSCAN grow clusters from dense regions, and model-based methods fit statistical models such as Gaussian mixtures.

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Which of the following can be used for clustering of data ?

A.Single layer perception
B.Multilayer perception
C.Self organizing map
D.Radial basis function

Exam Year(s)

UGC NET - 2012,

Answer: C

A self-organising map, or Kohonen map, learns without a teacher: nearby units in the map come to respond to similar inputs, so the map groups the data into clusters. A single layer perceptron and a multilayer perceptron are trained with target outputs for classification, and a radial basis function network also needs targets in its usual form, so these three are supervised classifiers. The answer is Self organizing map, option (C).

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